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Record W2908094064 · doi:10.5539/ijel.v9n1p54

Morphophonemic Variation in CaC-Initial Verb Structures in Kuwaiti Arabic

2018· article· en· W2908094064 on OpenAlexvenueno aff
Hanan A. Taqi

Bibliographic record

VenueInternational Journal of English Linguistics · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicLinguistic Variation and Morphology
Canadian institutionsnot available
Fundersnot available
KeywordsVerbRealisationVariation (astronomy)Ethnic groupLinguisticsArabicPrestigeVariety (cybernetics)Political scienceComputer scienceArtificial intelligencePhilosophyLawPhysics

Abstract

fetched live from OpenAlex

This study aims to investigate the linguistic and social factors influencing the realisation of the initial Modern Arabic verb form CaC-in Kuwaiti Arabic (KA). While very few studies have examined the sociolinguistic variation of the initial verb form CaC-in KA, this variable has been found to be produced in the speech of two Kuwaiti communities from different ethnic backgrounds, namely Najdi (from Saudi Arabia originally) and Ajami (from Iran originally). The aim is to analyse the realisation of CaC-forms as a reflection of ethnicity, age and gender in KA. Data were collected from 48 male and female Kuwaiti speakers from two ethnicities (Najdi and Ajami), three age groups (chosen according to relevant milestones in the history of Kuwait). Two main techniques were implemented to collect data in this study, namely spontaneous and controlled data. The investigation showed that there were significant differences in the realisation of the initial verb form CaC-in the two ethnicities and across age and gender. The study also showed that the CaC-form had less prestige than did the CiC-form, which is mostly found in the Najdi variety.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.339
Teacher spread0.318 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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Same venueInternational Journal of English LinguisticsSame topicLinguistic Variation and MorphologyFrench-language works237,207